Renesas / opencv-lib

openCV library for Renesas RZ/A

Dependents:   RZ_A2M_Mbed_samples

include/opencv2/stitching/detail/matchers.hpp@0:0e0631af0305, 2021-01-29 (annotated)

Committer:
RyoheiHagimoto
Date:
Fri Jan 29 04:53:38 2021 +0000
Revision:
0:0e0631af0305
copied from https://github.com/d-kato/opencv-lib.

Who changed what in which revision?

UserRevisionLine numberNew contents of line
RyoheiHagimoto 0:0e0631af0305 1 /*M///////////////////////////////////////////////////////////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 2 //
RyoheiHagimoto 0:0e0631af0305 3 // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
RyoheiHagimoto 0:0e0631af0305 4 //
RyoheiHagimoto 0:0e0631af0305 5 // By downloading, copying, installing or using the software you agree to this license.
RyoheiHagimoto 0:0e0631af0305 6 // If you do not agree to this license, do not download, install,
RyoheiHagimoto 0:0e0631af0305 7 // copy or use the software.
RyoheiHagimoto 0:0e0631af0305 8 //
RyoheiHagimoto 0:0e0631af0305 9 //
RyoheiHagimoto 0:0e0631af0305 10 // License Agreement
RyoheiHagimoto 0:0e0631af0305 11 // For Open Source Computer Vision Library
RyoheiHagimoto 0:0e0631af0305 12 //
RyoheiHagimoto 0:0e0631af0305 13 // Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
RyoheiHagimoto 0:0e0631af0305 14 // Copyright (C) 2009, Willow Garage Inc., all rights reserved.
RyoheiHagimoto 0:0e0631af0305 15 // Third party copyrights are property of their respective owners.
RyoheiHagimoto 0:0e0631af0305 16 //
RyoheiHagimoto 0:0e0631af0305 17 // Redistribution and use in source and binary forms, with or without modification,
RyoheiHagimoto 0:0e0631af0305 18 // are permitted provided that the following conditions are met:
RyoheiHagimoto 0:0e0631af0305 19 //
RyoheiHagimoto 0:0e0631af0305 20 // * Redistribution's of source code must retain the above copyright notice,
RyoheiHagimoto 0:0e0631af0305 21 // this list of conditions and the following disclaimer.
RyoheiHagimoto 0:0e0631af0305 22 //
RyoheiHagimoto 0:0e0631af0305 23 // * Redistribution's in binary form must reproduce the above copyright notice,
RyoheiHagimoto 0:0e0631af0305 24 // this list of conditions and the following disclaimer in the documentation
RyoheiHagimoto 0:0e0631af0305 25 // and/or other materials provided with the distribution.
RyoheiHagimoto 0:0e0631af0305 26 //
RyoheiHagimoto 0:0e0631af0305 27 // * The name of the copyright holders may not be used to endorse or promote products
RyoheiHagimoto 0:0e0631af0305 28 // derived from this software without specific prior written permission.
RyoheiHagimoto 0:0e0631af0305 29 //
RyoheiHagimoto 0:0e0631af0305 30 // This software is provided by the copyright holders and contributors "as is" and
RyoheiHagimoto 0:0e0631af0305 31 // any express or implied warranties, including, but not limited to, the implied
RyoheiHagimoto 0:0e0631af0305 32 // warranties of merchantability and fitness for a particular purpose are disclaimed.
RyoheiHagimoto 0:0e0631af0305 33 // In no event shall the Intel Corporation or contributors be liable for any direct,
RyoheiHagimoto 0:0e0631af0305 34 // indirect, incidental, special, exemplary, or consequential damages
RyoheiHagimoto 0:0e0631af0305 35 // (including, but not limited to, procurement of substitute goods or services;
RyoheiHagimoto 0:0e0631af0305 36 // loss of use, data, or profits; or business interruption) however caused
RyoheiHagimoto 0:0e0631af0305 37 // and on any theory of liability, whether in contract, strict liability,
RyoheiHagimoto 0:0e0631af0305 38 // or tort (including negligence or otherwise) arising in any way out of
RyoheiHagimoto 0:0e0631af0305 39 // the use of this software, even if advised of the possibility of such damage.
RyoheiHagimoto 0:0e0631af0305 40 //
RyoheiHagimoto 0:0e0631af0305 41 //M*/
RyoheiHagimoto 0:0e0631af0305 42
RyoheiHagimoto 0:0e0631af0305 43 #ifndef OPENCV_STITCHING_MATCHERS_HPP
RyoheiHagimoto 0:0e0631af0305 44 #define OPENCV_STITCHING_MATCHERS_HPP
RyoheiHagimoto 0:0e0631af0305 45
RyoheiHagimoto 0:0e0631af0305 46 #include "opencv2/core.hpp"
RyoheiHagimoto 0:0e0631af0305 47 #include "opencv2/features2d.hpp"
RyoheiHagimoto 0:0e0631af0305 48
RyoheiHagimoto 0:0e0631af0305 49 #include "opencv2/opencv_modules.hpp"
RyoheiHagimoto 0:0e0631af0305 50
RyoheiHagimoto 0:0e0631af0305 51 #ifdef HAVE_OPENCV_XFEATURES2D
RyoheiHagimoto 0:0e0631af0305 52 # include "opencv2/xfeatures2d/cuda.hpp"
RyoheiHagimoto 0:0e0631af0305 53 #endif
RyoheiHagimoto 0:0e0631af0305 54
RyoheiHagimoto 0:0e0631af0305 55 namespace cv {
RyoheiHagimoto 0:0e0631af0305 56 namespace detail {
RyoheiHagimoto 0:0e0631af0305 57
RyoheiHagimoto 0:0e0631af0305 58 //! @addtogroup stitching_match
RyoheiHagimoto 0:0e0631af0305 59 //! @{
RyoheiHagimoto 0:0e0631af0305 60
RyoheiHagimoto 0:0e0631af0305 61 /** @brief Structure containing image keypoints and descriptors. */
RyoheiHagimoto 0:0e0631af0305 62 struct CV_EXPORTS ImageFeatures
RyoheiHagimoto 0:0e0631af0305 63 {
RyoheiHagimoto 0:0e0631af0305 64 int img_idx;
RyoheiHagimoto 0:0e0631af0305 65 Size img_size;
RyoheiHagimoto 0:0e0631af0305 66 std::vector<KeyPoint> keypoints;
RyoheiHagimoto 0:0e0631af0305 67 UMat descriptors;
RyoheiHagimoto 0:0e0631af0305 68 };
RyoheiHagimoto 0:0e0631af0305 69
RyoheiHagimoto 0:0e0631af0305 70 /** @brief Feature finders base class */
RyoheiHagimoto 0:0e0631af0305 71 class CV_EXPORTS FeaturesFinder
RyoheiHagimoto 0:0e0631af0305 72 {
RyoheiHagimoto 0:0e0631af0305 73 public:
RyoheiHagimoto 0:0e0631af0305 74 virtual ~FeaturesFinder() {}
RyoheiHagimoto 0:0e0631af0305 75 /** @overload */
RyoheiHagimoto 0:0e0631af0305 76 void operator ()(InputArray image, ImageFeatures &features);
RyoheiHagimoto 0:0e0631af0305 77 /** @brief Finds features in the given image.
RyoheiHagimoto 0:0e0631af0305 78
RyoheiHagimoto 0:0e0631af0305 79 @param image Source image
RyoheiHagimoto 0:0e0631af0305 80 @param features Found features
RyoheiHagimoto 0:0e0631af0305 81 @param rois Regions of interest
RyoheiHagimoto 0:0e0631af0305 82
RyoheiHagimoto 0:0e0631af0305 83 @sa detail::ImageFeatures, Rect_
RyoheiHagimoto 0:0e0631af0305 84 */
RyoheiHagimoto 0:0e0631af0305 85 void operator ()(InputArray image, ImageFeatures &features, const std::vector<cv::Rect> &rois);
RyoheiHagimoto 0:0e0631af0305 86 /** @brief Finds features in the given images in parallel.
RyoheiHagimoto 0:0e0631af0305 87
RyoheiHagimoto 0:0e0631af0305 88 @param images Source images
RyoheiHagimoto 0:0e0631af0305 89 @param features Found features for each image
RyoheiHagimoto 0:0e0631af0305 90 @param rois Regions of interest for each image
RyoheiHagimoto 0:0e0631af0305 91
RyoheiHagimoto 0:0e0631af0305 92 @sa detail::ImageFeatures, Rect_
RyoheiHagimoto 0:0e0631af0305 93 */
RyoheiHagimoto 0:0e0631af0305 94 void operator ()(InputArrayOfArrays images, std::vector<ImageFeatures> &features,
RyoheiHagimoto 0:0e0631af0305 95 const std::vector<std::vector<cv::Rect> > &rois);
RyoheiHagimoto 0:0e0631af0305 96 /** @overload */
RyoheiHagimoto 0:0e0631af0305 97 void operator ()(InputArrayOfArrays images, std::vector<ImageFeatures> &features);
RyoheiHagimoto 0:0e0631af0305 98 /** @brief Frees unused memory allocated before if there is any. */
RyoheiHagimoto 0:0e0631af0305 99 virtual void collectGarbage() {}
RyoheiHagimoto 0:0e0631af0305 100
RyoheiHagimoto 0:0e0631af0305 101 /* TODO OpenCV ABI 4.x
RyoheiHagimoto 0:0e0631af0305 102 reimplement this as public method similar to FeaturesMatcher and remove private function hack
RyoheiHagimoto 0:0e0631af0305 103 @return True, if it's possible to use the same finder instance in parallel, false otherwise
RyoheiHagimoto 0:0e0631af0305 104 bool isThreadSafe() const { return is_thread_safe_; }
RyoheiHagimoto 0:0e0631af0305 105 */
RyoheiHagimoto 0:0e0631af0305 106
RyoheiHagimoto 0:0e0631af0305 107 protected:
RyoheiHagimoto 0:0e0631af0305 108 /** @brief This method must implement features finding logic in order to make the wrappers
RyoheiHagimoto 0:0e0631af0305 109 detail::FeaturesFinder::operator()_ work.
RyoheiHagimoto 0:0e0631af0305 110
RyoheiHagimoto 0:0e0631af0305 111 @param image Source image
RyoheiHagimoto 0:0e0631af0305 112 @param features Found features
RyoheiHagimoto 0:0e0631af0305 113
RyoheiHagimoto 0:0e0631af0305 114 @sa detail::ImageFeatures */
RyoheiHagimoto 0:0e0631af0305 115 virtual void find(InputArray image, ImageFeatures &features) = 0;
RyoheiHagimoto 0:0e0631af0305 116 /** @brief uses dynamic_cast to determine thread-safety
RyoheiHagimoto 0:0e0631af0305 117 @return True, if it's possible to use the same finder instance in parallel, false otherwise
RyoheiHagimoto 0:0e0631af0305 118 */
RyoheiHagimoto 0:0e0631af0305 119 bool isThreadSafe() const;
RyoheiHagimoto 0:0e0631af0305 120 };
RyoheiHagimoto 0:0e0631af0305 121
RyoheiHagimoto 0:0e0631af0305 122 /** @brief SURF features finder.
RyoheiHagimoto 0:0e0631af0305 123
RyoheiHagimoto 0:0e0631af0305 124 @sa detail::FeaturesFinder, SURF
RyoheiHagimoto 0:0e0631af0305 125 */
RyoheiHagimoto 0:0e0631af0305 126 class CV_EXPORTS SurfFeaturesFinder : public FeaturesFinder
RyoheiHagimoto 0:0e0631af0305 127 {
RyoheiHagimoto 0:0e0631af0305 128 public:
RyoheiHagimoto 0:0e0631af0305 129 SurfFeaturesFinder(double hess_thresh = 300., int num_octaves = 3, int num_layers = 4,
RyoheiHagimoto 0:0e0631af0305 130 int num_octaves_descr = /*4*/3, int num_layers_descr = /*2*/4);
RyoheiHagimoto 0:0e0631af0305 131
RyoheiHagimoto 0:0e0631af0305 132 private:
RyoheiHagimoto 0:0e0631af0305 133 void find(InputArray image, ImageFeatures &features);
RyoheiHagimoto 0:0e0631af0305 134
RyoheiHagimoto 0:0e0631af0305 135 Ptr<FeatureDetector> detector_;
RyoheiHagimoto 0:0e0631af0305 136 Ptr<DescriptorExtractor> extractor_;
RyoheiHagimoto 0:0e0631af0305 137 Ptr<Feature2D> surf;
RyoheiHagimoto 0:0e0631af0305 138 };
RyoheiHagimoto 0:0e0631af0305 139
RyoheiHagimoto 0:0e0631af0305 140 /** @brief ORB features finder. :
RyoheiHagimoto 0:0e0631af0305 141
RyoheiHagimoto 0:0e0631af0305 142 @sa detail::FeaturesFinder, ORB
RyoheiHagimoto 0:0e0631af0305 143 */
RyoheiHagimoto 0:0e0631af0305 144 class CV_EXPORTS OrbFeaturesFinder : public FeaturesFinder
RyoheiHagimoto 0:0e0631af0305 145 {
RyoheiHagimoto 0:0e0631af0305 146 public:
RyoheiHagimoto 0:0e0631af0305 147 OrbFeaturesFinder(Size _grid_size = Size(3,1), int nfeatures=1500, float scaleFactor=1.3f, int nlevels=5);
RyoheiHagimoto 0:0e0631af0305 148
RyoheiHagimoto 0:0e0631af0305 149 private:
RyoheiHagimoto 0:0e0631af0305 150 void find(InputArray image, ImageFeatures &features);
RyoheiHagimoto 0:0e0631af0305 151
RyoheiHagimoto 0:0e0631af0305 152 Ptr<ORB> orb;
RyoheiHagimoto 0:0e0631af0305 153 Size grid_size;
RyoheiHagimoto 0:0e0631af0305 154 };
RyoheiHagimoto 0:0e0631af0305 155
RyoheiHagimoto 0:0e0631af0305 156 /** @brief AKAZE features finder. :
RyoheiHagimoto 0:0e0631af0305 157
RyoheiHagimoto 0:0e0631af0305 158 @sa detail::FeaturesFinder, AKAZE
RyoheiHagimoto 0:0e0631af0305 159 */
RyoheiHagimoto 0:0e0631af0305 160 class CV_EXPORTS AKAZEFeaturesFinder : public detail::FeaturesFinder
RyoheiHagimoto 0:0e0631af0305 161 {
RyoheiHagimoto 0:0e0631af0305 162 public:
RyoheiHagimoto 0:0e0631af0305 163 AKAZEFeaturesFinder(int descriptor_type = AKAZE::DESCRIPTOR_MLDB,
RyoheiHagimoto 0:0e0631af0305 164 int descriptor_size = 0,
RyoheiHagimoto 0:0e0631af0305 165 int descriptor_channels = 3,
RyoheiHagimoto 0:0e0631af0305 166 float threshold = 0.001f,
RyoheiHagimoto 0:0e0631af0305 167 int nOctaves = 4,
RyoheiHagimoto 0:0e0631af0305 168 int nOctaveLayers = 4,
RyoheiHagimoto 0:0e0631af0305 169 int diffusivity = KAZE::DIFF_PM_G2);
RyoheiHagimoto 0:0e0631af0305 170
RyoheiHagimoto 0:0e0631af0305 171 private:
RyoheiHagimoto 0:0e0631af0305 172 void find(InputArray image, detail::ImageFeatures &features);
RyoheiHagimoto 0:0e0631af0305 173
RyoheiHagimoto 0:0e0631af0305 174 Ptr<AKAZE> akaze;
RyoheiHagimoto 0:0e0631af0305 175 };
RyoheiHagimoto 0:0e0631af0305 176
RyoheiHagimoto 0:0e0631af0305 177 #ifdef HAVE_OPENCV_XFEATURES2D
RyoheiHagimoto 0:0e0631af0305 178 class CV_EXPORTS SurfFeaturesFinderGpu : public FeaturesFinder
RyoheiHagimoto 0:0e0631af0305 179 {
RyoheiHagimoto 0:0e0631af0305 180 public:
RyoheiHagimoto 0:0e0631af0305 181 SurfFeaturesFinderGpu(double hess_thresh = 300., int num_octaves = 3, int num_layers = 4,
RyoheiHagimoto 0:0e0631af0305 182 int num_octaves_descr = 4, int num_layers_descr = 2);
RyoheiHagimoto 0:0e0631af0305 183
RyoheiHagimoto 0:0e0631af0305 184 void collectGarbage();
RyoheiHagimoto 0:0e0631af0305 185
RyoheiHagimoto 0:0e0631af0305 186 private:
RyoheiHagimoto 0:0e0631af0305 187 void find(InputArray image, ImageFeatures &features);
RyoheiHagimoto 0:0e0631af0305 188
RyoheiHagimoto 0:0e0631af0305 189 cuda::GpuMat image_;
RyoheiHagimoto 0:0e0631af0305 190 cuda::GpuMat gray_image_;
RyoheiHagimoto 0:0e0631af0305 191 cuda::SURF_CUDA surf_;
RyoheiHagimoto 0:0e0631af0305 192 cuda::GpuMat keypoints_;
RyoheiHagimoto 0:0e0631af0305 193 cuda::GpuMat descriptors_;
RyoheiHagimoto 0:0e0631af0305 194 int num_octaves_, num_layers_;
RyoheiHagimoto 0:0e0631af0305 195 int num_octaves_descr_, num_layers_descr_;
RyoheiHagimoto 0:0e0631af0305 196 };
RyoheiHagimoto 0:0e0631af0305 197 #endif
RyoheiHagimoto 0:0e0631af0305 198
RyoheiHagimoto 0:0e0631af0305 199 /** @brief Structure containing information about matches between two images.
RyoheiHagimoto 0:0e0631af0305 200
RyoheiHagimoto 0:0e0631af0305 201 It's assumed that there is a transformation between those images. Transformation may be
RyoheiHagimoto 0:0e0631af0305 202 homography or affine transformation based on selected matcher.
RyoheiHagimoto 0:0e0631af0305 203
RyoheiHagimoto 0:0e0631af0305 204 @sa detail::FeaturesMatcher
RyoheiHagimoto 0:0e0631af0305 205 */
RyoheiHagimoto 0:0e0631af0305 206 struct CV_EXPORTS MatchesInfo
RyoheiHagimoto 0:0e0631af0305 207 {
RyoheiHagimoto 0:0e0631af0305 208 MatchesInfo();
RyoheiHagimoto 0:0e0631af0305 209 MatchesInfo(const MatchesInfo &other);
RyoheiHagimoto 0:0e0631af0305 210 const MatchesInfo& operator =(const MatchesInfo &other);
RyoheiHagimoto 0:0e0631af0305 211
RyoheiHagimoto 0:0e0631af0305 212 int src_img_idx, dst_img_idx; //!< Images indices (optional)
RyoheiHagimoto 0:0e0631af0305 213 std::vector<DMatch> matches;
RyoheiHagimoto 0:0e0631af0305 214 std::vector<uchar> inliers_mask; //!< Geometrically consistent matches mask
RyoheiHagimoto 0:0e0631af0305 215 int num_inliers; //!< Number of geometrically consistent matches
RyoheiHagimoto 0:0e0631af0305 216 Mat H; //!< Estimated transformation
RyoheiHagimoto 0:0e0631af0305 217 double confidence; //!< Confidence two images are from the same panorama
RyoheiHagimoto 0:0e0631af0305 218 };
RyoheiHagimoto 0:0e0631af0305 219
RyoheiHagimoto 0:0e0631af0305 220 /** @brief Feature matchers base class. */
RyoheiHagimoto 0:0e0631af0305 221 class CV_EXPORTS FeaturesMatcher
RyoheiHagimoto 0:0e0631af0305 222 {
RyoheiHagimoto 0:0e0631af0305 223 public:
RyoheiHagimoto 0:0e0631af0305 224 virtual ~FeaturesMatcher() {}
RyoheiHagimoto 0:0e0631af0305 225
RyoheiHagimoto 0:0e0631af0305 226 /** @overload
RyoheiHagimoto 0:0e0631af0305 227 @param features1 First image features
RyoheiHagimoto 0:0e0631af0305 228 @param features2 Second image features
RyoheiHagimoto 0:0e0631af0305 229 @param matches_info Found matches
RyoheiHagimoto 0:0e0631af0305 230 */
RyoheiHagimoto 0:0e0631af0305 231 void operator ()(const ImageFeatures &features1, const ImageFeatures &features2,
RyoheiHagimoto 0:0e0631af0305 232 MatchesInfo& matches_info) { match(features1, features2, matches_info); }
RyoheiHagimoto 0:0e0631af0305 233
RyoheiHagimoto 0:0e0631af0305 234 /** @brief Performs images matching.
RyoheiHagimoto 0:0e0631af0305 235
RyoheiHagimoto 0:0e0631af0305 236 @param features Features of the source images
RyoheiHagimoto 0:0e0631af0305 237 @param pairwise_matches Found pairwise matches
RyoheiHagimoto 0:0e0631af0305 238 @param mask Mask indicating which image pairs must be matched
RyoheiHagimoto 0:0e0631af0305 239
RyoheiHagimoto 0:0e0631af0305 240 The function is parallelized with the TBB library.
RyoheiHagimoto 0:0e0631af0305 241
RyoheiHagimoto 0:0e0631af0305 242 @sa detail::MatchesInfo
RyoheiHagimoto 0:0e0631af0305 243 */
RyoheiHagimoto 0:0e0631af0305 244 void operator ()(const std::vector<ImageFeatures> &features, std::vector<MatchesInfo> &pairwise_matches,
RyoheiHagimoto 0:0e0631af0305 245 const cv::UMat &mask = cv::UMat());
RyoheiHagimoto 0:0e0631af0305 246
RyoheiHagimoto 0:0e0631af0305 247 /** @return True, if it's possible to use the same matcher instance in parallel, false otherwise
RyoheiHagimoto 0:0e0631af0305 248 */
RyoheiHagimoto 0:0e0631af0305 249 bool isThreadSafe() const { return is_thread_safe_; }
RyoheiHagimoto 0:0e0631af0305 250
RyoheiHagimoto 0:0e0631af0305 251 /** @brief Frees unused memory allocated before if there is any.
RyoheiHagimoto 0:0e0631af0305 252 */
RyoheiHagimoto 0:0e0631af0305 253 virtual void collectGarbage() {}
RyoheiHagimoto 0:0e0631af0305 254
RyoheiHagimoto 0:0e0631af0305 255 protected:
RyoheiHagimoto 0:0e0631af0305 256 FeaturesMatcher(bool is_thread_safe = false) : is_thread_safe_(is_thread_safe) {}
RyoheiHagimoto 0:0e0631af0305 257
RyoheiHagimoto 0:0e0631af0305 258 /** @brief This method must implement matching logic in order to make the wrappers
RyoheiHagimoto 0:0e0631af0305 259 detail::FeaturesMatcher::operator()_ work.
RyoheiHagimoto 0:0e0631af0305 260
RyoheiHagimoto 0:0e0631af0305 261 @param features1 first image features
RyoheiHagimoto 0:0e0631af0305 262 @param features2 second image features
RyoheiHagimoto 0:0e0631af0305 263 @param matches_info found matches
RyoheiHagimoto 0:0e0631af0305 264 */
RyoheiHagimoto 0:0e0631af0305 265 virtual void match(const ImageFeatures &features1, const ImageFeatures &features2,
RyoheiHagimoto 0:0e0631af0305 266 MatchesInfo& matches_info) = 0;
RyoheiHagimoto 0:0e0631af0305 267
RyoheiHagimoto 0:0e0631af0305 268 bool is_thread_safe_;
RyoheiHagimoto 0:0e0631af0305 269 };
RyoheiHagimoto 0:0e0631af0305 270
RyoheiHagimoto 0:0e0631af0305 271 /** @brief Features matcher which finds two best matches for each feature and leaves the best one only if the
RyoheiHagimoto 0:0e0631af0305 272 ratio between descriptor distances is greater than the threshold match_conf
RyoheiHagimoto 0:0e0631af0305 273
RyoheiHagimoto 0:0e0631af0305 274 @sa detail::FeaturesMatcher
RyoheiHagimoto 0:0e0631af0305 275 */
RyoheiHagimoto 0:0e0631af0305 276 class CV_EXPORTS BestOf2NearestMatcher : public FeaturesMatcher
RyoheiHagimoto 0:0e0631af0305 277 {
RyoheiHagimoto 0:0e0631af0305 278 public:
RyoheiHagimoto 0:0e0631af0305 279 /** @brief Constructs a "best of 2 nearest" matcher.
RyoheiHagimoto 0:0e0631af0305 280
RyoheiHagimoto 0:0e0631af0305 281 @param try_use_gpu Should try to use GPU or not
RyoheiHagimoto 0:0e0631af0305 282 @param match_conf Match distances ration threshold
RyoheiHagimoto 0:0e0631af0305 283 @param num_matches_thresh1 Minimum number of matches required for the 2D projective transform
RyoheiHagimoto 0:0e0631af0305 284 estimation used in the inliers classification step
RyoheiHagimoto 0:0e0631af0305 285 @param num_matches_thresh2 Minimum number of matches required for the 2D projective transform
RyoheiHagimoto 0:0e0631af0305 286 re-estimation on inliers
RyoheiHagimoto 0:0e0631af0305 287 */
RyoheiHagimoto 0:0e0631af0305 288 BestOf2NearestMatcher(bool try_use_gpu = false, float match_conf = 0.3f, int num_matches_thresh1 = 6,
RyoheiHagimoto 0:0e0631af0305 289 int num_matches_thresh2 = 6);
RyoheiHagimoto 0:0e0631af0305 290
RyoheiHagimoto 0:0e0631af0305 291 void collectGarbage();
RyoheiHagimoto 0:0e0631af0305 292
RyoheiHagimoto 0:0e0631af0305 293 protected:
RyoheiHagimoto 0:0e0631af0305 294 void match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo &matches_info);
RyoheiHagimoto 0:0e0631af0305 295
RyoheiHagimoto 0:0e0631af0305 296 int num_matches_thresh1_;
RyoheiHagimoto 0:0e0631af0305 297 int num_matches_thresh2_;
RyoheiHagimoto 0:0e0631af0305 298 Ptr<FeaturesMatcher> impl_;
RyoheiHagimoto 0:0e0631af0305 299 };
RyoheiHagimoto 0:0e0631af0305 300
RyoheiHagimoto 0:0e0631af0305 301 class CV_EXPORTS BestOf2NearestRangeMatcher : public BestOf2NearestMatcher
RyoheiHagimoto 0:0e0631af0305 302 {
RyoheiHagimoto 0:0e0631af0305 303 public:
RyoheiHagimoto 0:0e0631af0305 304 BestOf2NearestRangeMatcher(int range_width = 5, bool try_use_gpu = false, float match_conf = 0.3f,
RyoheiHagimoto 0:0e0631af0305 305 int num_matches_thresh1 = 6, int num_matches_thresh2 = 6);
RyoheiHagimoto 0:0e0631af0305 306
RyoheiHagimoto 0:0e0631af0305 307 void operator ()(const std::vector<ImageFeatures> &features, std::vector<MatchesInfo> &pairwise_matches,
RyoheiHagimoto 0:0e0631af0305 308 const cv::UMat &mask = cv::UMat());
RyoheiHagimoto 0:0e0631af0305 309
RyoheiHagimoto 0:0e0631af0305 310
RyoheiHagimoto 0:0e0631af0305 311 protected:
RyoheiHagimoto 0:0e0631af0305 312 int range_width_;
RyoheiHagimoto 0:0e0631af0305 313 };
RyoheiHagimoto 0:0e0631af0305 314
RyoheiHagimoto 0:0e0631af0305 315 /** @brief Features matcher similar to cv::detail::BestOf2NearestMatcher which
RyoheiHagimoto 0:0e0631af0305 316 finds two best matches for each feature and leaves the best one only if the
RyoheiHagimoto 0:0e0631af0305 317 ratio between descriptor distances is greater than the threshold match_conf.
RyoheiHagimoto 0:0e0631af0305 318
RyoheiHagimoto 0:0e0631af0305 319 Unlike cv::detail::BestOf2NearestMatcher this matcher uses affine
RyoheiHagimoto 0:0e0631af0305 320 transformation (affine trasformation estimate will be placed in matches_info).
RyoheiHagimoto 0:0e0631af0305 321
RyoheiHagimoto 0:0e0631af0305 322 @sa cv::detail::FeaturesMatcher cv::detail::BestOf2NearestMatcher
RyoheiHagimoto 0:0e0631af0305 323 */
RyoheiHagimoto 0:0e0631af0305 324 class CV_EXPORTS AffineBestOf2NearestMatcher : public BestOf2NearestMatcher
RyoheiHagimoto 0:0e0631af0305 325 {
RyoheiHagimoto 0:0e0631af0305 326 public:
RyoheiHagimoto 0:0e0631af0305 327 /** @brief Constructs a "best of 2 nearest" matcher that expects affine trasformation
RyoheiHagimoto 0:0e0631af0305 328 between images
RyoheiHagimoto 0:0e0631af0305 329
RyoheiHagimoto 0:0e0631af0305 330 @param full_affine whether to use full affine transformation with 6 degress of freedom or reduced
RyoheiHagimoto 0:0e0631af0305 331 transformation with 4 degrees of freedom using only rotation, translation and uniform scaling
RyoheiHagimoto 0:0e0631af0305 332 @param try_use_gpu Should try to use GPU or not
RyoheiHagimoto 0:0e0631af0305 333 @param match_conf Match distances ration threshold
RyoheiHagimoto 0:0e0631af0305 334 @param num_matches_thresh1 Minimum number of matches required for the 2D affine transform
RyoheiHagimoto 0:0e0631af0305 335 estimation used in the inliers classification step
RyoheiHagimoto 0:0e0631af0305 336
RyoheiHagimoto 0:0e0631af0305 337 @sa cv::estimateAffine2D cv::estimateAffinePartial2D
RyoheiHagimoto 0:0e0631af0305 338 */
RyoheiHagimoto 0:0e0631af0305 339 AffineBestOf2NearestMatcher(bool full_affine = false, bool try_use_gpu = false,
RyoheiHagimoto 0:0e0631af0305 340 float match_conf = 0.3f, int num_matches_thresh1 = 6) :
RyoheiHagimoto 0:0e0631af0305 341 BestOf2NearestMatcher(try_use_gpu, match_conf, num_matches_thresh1, num_matches_thresh1),
RyoheiHagimoto 0:0e0631af0305 342 full_affine_(full_affine) {}
RyoheiHagimoto 0:0e0631af0305 343
RyoheiHagimoto 0:0e0631af0305 344 protected:
RyoheiHagimoto 0:0e0631af0305 345 void match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo &matches_info);
RyoheiHagimoto 0:0e0631af0305 346
RyoheiHagimoto 0:0e0631af0305 347 bool full_affine_;
RyoheiHagimoto 0:0e0631af0305 348 };
RyoheiHagimoto 0:0e0631af0305 349
RyoheiHagimoto 0:0e0631af0305 350 //! @} stitching_match
RyoheiHagimoto 0:0e0631af0305 351
RyoheiHagimoto 0:0e0631af0305 352 } // namespace detail
RyoheiHagimoto 0:0e0631af0305 353 } // namespace cv
RyoheiHagimoto 0:0e0631af0305 354
RyoheiHagimoto 0:0e0631af0305 355 #endif // OPENCV_STITCHING_MATCHERS_HPP